Leading AI Adoption
For the managers, directors and initiative leads who decide how AI gets used in their organisation. Covers setting direction by example, building a roadmap, connecting AI to business value, governing it as it scales, leading adoption, designing workflows, testing for reliability and handing over what works. Judgment and decision-making, not machine learning.
Leading by Example: Using AI Yourself and Setting Direction
0/2Credibility comes from doing the work on approved material, checking it and being open about what helped. Then direction: what AI is for, what is approved and what is off limits.
Shaping the AI Roadmap
0/2Start from what is already in use, sequence by value, risk and readiness, and write the stop criteria before the first pilot.
From Use Case to Business Value
0/2Specific outcomes, honest baselines, and a value story that says what the evidence shows and what it does not.
Governing AI as It Scales
0/2Named owners, decision rights, controls matched to consequence, and what needs a sponsor's decision.
Leading Adoption and Bringing People Along
0/2Matching support to where people actually are: first trials, repeat use, changed work. Training, resistance and informing the workforce.
Designing AI-Supported Workflows
0/2Where the tool drafts and where a person decides, what data goes in, where review sits and what happens when it fails.
Building and Testing Dependable AI Solutions
0/2Testing beyond the routine cases, criteria set in advance, and deciding what to do when the evidence is incomplete.
Running What Works: Handoff and Operations
0/2Handing a workflow to a team that did not build it: owner, maintainer, support route, change control and review triggers.
Final assessment
20 questions drawn so that no two attempts share a question, 60 minutes, 75% to pass. Up to 3 attempts with 24 hours between them. Passing issues a Certificate of Completion.
Unlocks when every lesson is marked complete. 0 of 16 done, 16 to go.